With increasing digitisation of power systems, and more data available than ever before to system operators, refining these streams of data into a usable and actionable format is a significant challenge.
There are often uncertainties in the data itself, and data formats may not always be straightforward to integrate into useful information. Too little information can be misleading or uninformative, but too much can be overwhelming.
Understanding not only which data to communicate, but how, affects not only network operators but policymakers and other stakeholders who are held accountable for when the results of these decisions manifest, such as when the power outages following Storm Arwen happened in 2021. Decisions made ahead of these events, and afterwards, should be defensible and made on the basis of the best available information.
If we understand risk as a function of likelihood and impact, therefore, we should present information in a way which clearly identifies these separate components but combines them in an informative way.
The aims of the project were:
This project involved taking historic weather data from NASA and combining it with system data for the 33kV and 11kV system in Western Aberdeenshire from SHEPD, then using statistical modelling of outage probability on towers on this system to project failure probabilities, impact, and risk during an extreme weather event.
This data was then presented in various formats to communicate the most pertinent and important information which emerged from the results of the undertaken simulations and to investigate the different potential means of communicating information gleaned from a complicated combination of multiple datasets.
Why did we undertake this project?
This forms part of the Future Control Room workstream and is intended to contribute to demonstrating concepts which should be used in a future where data-driven risk assessments become increasingly deployed in operational scenarios to support expert knowledge and improve decision-making and accountability.
Research was conducted using a desktop-based simulation.
PNDC developed the simulation model used, and consolidated data from a wide range of sources, culminating in the code base developed and a report which investigates data visualisation as a state of the art within the sector and how it is being approached within industry and academia.
The simulation performed investigated the peak of Storm Arwen and based on the probabilities calculated within the simulation, suggested that over 100,000 customers in the studied network would suffer power outages. This analysis was based on assumptions regarding how many customers are using power, and assuming lines with a greater than 50% probability of faulting fell out of service during the storm.
The data generated via the simulation was represented in multiple formats for user interaction and to demonstrate the types of information and visualisations which could be created from the modelling.
Outcomes & Impact
PNDC provided the expert knowledge in data management, cleansing, processing, and HILP event modelling to generate the models used and demonstrate model applications. This codebase and the elements generated can be used to optimise planning decisions such as placement of spare parts or emergency response teams to, for example:
Aid reduction in Customer Minutes Lost (CML) or Customer Interruptions (CL).
Reduce the amount of people impacted.
Reduce costs of interventions.
Improve data and information provided to stakeholders ahead of large scale events.
Serrano-Fontova, A., Li, H., Liao, Z., Jamieson, M.R., Serrano, R., Parisio, A. and Panteli, M., 2023. A comprehensive review and comparison of the fragility curves used for resilience assessments in power systems. IEEE Access.
Jamieson, M.R., Strbac, G. and Bell, K.R., 2020. Quantification and visualisation of extreme wind effects on transmission network outage probability and wind generation output. IET Smart Grid, 3(2), pp.112-122.
Jamieson, M.R., Hong, Q., Han, J., Paladhi, S. and Booth, C., 2022. Digital twin-based real-time assessment of resilience in microgrids.
Liao, Z., Serrano-Fontova, A., Li, H. and Jamieson, M.R., 2023, May. The influence of fragility curves in Resilience Assessments considering windstorms: A sensitivity analysis. In 2023 IEEE PES GTD International Conference and Exposition (GTD) (pp. 361-365). IEEE.
Get in touch
PNDC project leads: Dr Magnus R.Jamieson and Dr Kyle Jennett.
For further information on this case study or to discuss collaborative opportunities, please get in touch.
PNDC is one of the University of Strathclyde’s industry-facing innovation centres and focuses on accelerating the development and deployment of novel energy and transport technologies through multiple collaboration models and open access facility provision.